The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern
Autor: | Olga Ivanova, Annika Jacobsen, Jaap Heringa, Patrick Kemmeren, Philip Lijnzaad, Saman Amini, Frank C. P. Holstege, K. Anton Feenstra |
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Přispěvatelé: | Bioinformatics, Computer Science, AIMMS, Integrative Bioinformatics |
Jazyk: | angličtina |
Rok vydání: | 2019 |
Předmět: |
0301 basic medicine
Mutagenesis and Gene Deletion Techniques Mutant Gene Identification and Analysis Gene Expression Biochemistry Inversion (linguistics) 0302 clinical medicine Gene expression Databases Genetic Biology (General) Regulation of gene expression 0303 health sciences Ecology Kinase Enzymes Computational Theory and Mathematics Mechanism (philosophy) Modeling and Simulation Research Article Signal Transduction QH301-705.5 DNA transcription Genes Fungal Computational biology Saccharomyces cerevisiae Biology Research and Analysis Methods Cellular and Molecular Neuroscience 03 medical and health sciences Gene Types Genetic variation DNA-binding proteins Genetics Gene Regulation Computer Simulation Molecular Biology Techniques Transcription factor Gene Molecular Biology Ecology Evolution Behavior and Systematics Genetic Association Studies 030304 developmental biology Models Genetic Deletion Mutagenesis Phosphatases Inversion (evolutionary biology) Biology and Life Sciences Proteins Computational Biology Epistasis Genetic Regulatory Proteins 030104 developmental biology Genetic Interactions Gene Expression Regulation Chromosome Inversion Mutation Enzymology Regulator Genes 030217 neurology & neurosurgery Transcription Factors |
Zdroj: | PLoS Computational Biology Amini, S, Jacobsen, A, Ivanova, O, Lijnzaad, P, Heringa, J, Holstege, F C P, Feenstra, K A & Kemmeren, P 2019, ' The ability of transcription factors to differentially regulate gene expression is a crucial component of the mechanism underlying inversion, a frequently observed genetic interaction pattern ', PLoS Computational Biology, vol. 15, no. 5, e1007061, pp. 1-27 . https://doi.org/10.1371/journal.pcbi.1007061 PLoS Computational Biology, Vol 15, Iss 5, p e1007061 (2019) PLoS Computational Biology, 15(5):e1007061, 1-27. Public Library of Science |
ISSN: | 1553-7358 1553-734X |
Popis: | Genetic interactions, a phenomenon whereby combinations of mutations lead to unexpected effects, reflect how cellular processes are wired and play an important role in complex genetic diseases. Understanding the molecular basis of genetic interactions is crucial for deciphering pathway organization as well as understanding the relationship between genetic variation and disease. Several hypothetical molecular mechanisms have been linked to different genetic interaction types. However, differences in genetic interaction patterns and their underlying mechanisms have not yet been compared systematically between different functional gene classes. Here, differences in the occurrence and types of genetic interactions are compared for two classes, gene-specific transcription factors (GSTFs) and signaling genes (kinases and phosphatases). Genome-wide gene expression data for 63 single and double deletion mutants in baker’s yeast reveals that the two most common genetic interaction patterns are buffering and inversion. Buffering is typically associated with redundancy and is well understood. In inversion, genes show opposite behavior in the double mutant compared to the corresponding single mutants. The underlying mechanism is poorly understood. Although both classes show buffering and inversion patterns, the prevalence of inversion is much stronger in GSTFs. To decipher potential mechanisms, a Petri Net modeling approach was employed, where genes are represented as nodes and relationships between genes as edges. This allowed over 9 million possible three and four node models to be exhaustively enumerated. The models show that a quantitative difference in interaction strength is a strict requirement for obtaining inversion. In addition, this difference is frequently accompanied with a second gene that shows buffering. Taken together, these results provide a mechanistic explanation for inversion. Furthermore, the ability of transcription factors to differentially regulate expression of their targets provides a likely explanation why inversion is more prevalent for GSTFs compared to kinases and phosphatases. Author summary The relationship between genotype and phenotype is one of the major challenges in biology. While many previous studies have identified genes involved in complex genetic diseases, there is still a gap between genotype and phenotype. One of the difficulties in filling this gap has been attributed to genetic interactions. Large-scale studies have revealed that genetic interactions are widespread in model organisms such as baker’s yeast. Several molecular mechanisms have been proposed for different genetic interaction types. However, differences in occurrence and underlying molecular mechanism of genetic interactions have not yet been compared between gene classes of different function. Here, we compared genetic interaction patterns identified using gene expression profiling for two classes of genes: gene specific transcription factors and signaling related genes. We modelled all possible molecular networks to unravel putative molecular differences underlying different genetic interaction patterns. Our study proposes a new mechanistic explanation for a certain genetic interaction pattern that is more strongly associated with transcription factors compared to signaling related genes. Overall, our findings and the computational methodologies implemented here can be valuable for understanding the molecular mechanisms underlying genetic interactions. |
Databáze: | OpenAIRE |
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